There is also the social aspect of these developments. On the one side, companies involved with artificial intelligence technologies pop up like mushrooms in a rainforest. On the other side, more and more people are becoming worried about their jobs or livelihoods.
Nvidia Corporation is one of those companies that has been riding the crest of the artificial intelligence boom. For those who haven’t heard yet, shares of Nvidia skyrocketed in a very short time.
The financial analyses of the success are available all around the internet. They are out of our scope, but to summarize, Nvidia stocks skyrocketed, and the company’s value increased by around 25%. That was one of the highest value increases in history and increased Nvidia’s value by approximately 200 billion dollars. (196 billion dollars, to be more precise.)
For a while, shares of Nvidia even surpassed the one trillion dollar mark, temporarily making Nvidia join a group of very exclusive companies. The Nvidia shares settled at a slightly lower value, and the company value landed around 940 billion dollars.
Nvidia has a fierce rivalry with AMD (Advanced Micro Devices), or AMD’s graphics card branch, formerly known as ATI. Similar to the rivalry between Intel and AMD, this rivalry has a long and checkered history for both sides. Thanks to the boost that Lisa Su’s arrival at AMD created, Nvidia seemed to become shortwinded. But after this surge in Nvidia’s stock value, it looks like it will compete in a league of its own for a while. But with this surge in Nvidia’s stock value, it looks like it will compete in a league of its own for a while.
What happened to Nvidia shares besides breaking a couple of financial history records? What made Nvidia shares skyrocket and achieve the incredible result it did? What is the story behind it, and most importantly, what does artificial intelligence or AI gaming do with Nvidia’s stock rise?
Nvidia and artificial intelligence
Enthusiasts of cryptocurrencies will remember that when the crypto mining rush was on, graphic cards were the focus of the rush. It even affected the graphic card prices during its peak, and again, graphic card prices fell after the crypto mining rush died out. This was due to crypto mining requiring very high processing power because of the nature of the mining process. Although CPUs also have very high processing powers, the fundamental structure and purpose of GPUs make them more efficient in crypto mining.
Similarly, GPU chips are also very efficient when used in artificial intelligence technologies. To put it in the simplest way possible, CPUs are built to execute multiple tasks that may require different calculations or processes. In contrast, GPUs are built to complete a relatively limited range of repetitive tasks as quickly as possible. This fundamental structure makes GPUs far more efficient in processing massive amounts of data to train generative AI or other types of artificial intelligence programs like the renowned ChatGPT or Google PaLM 2.
Artificial intelligence is basically software designed to mimic human intelligence in various aspects. And like all software, it needs adequate and powerful hardware to run efficiently and smoothly. Companies working on artificial intelligence have relied on graphic card chips for years to meet this hardware requirement. With the increase in the number of artificial intelligence startups and some of the earlier startups taking steps to become giant tech companies, it’s easy to predict that the demand will increase, affecting Nvidia stock prices.
Now add the fact that a set of eight of these chips can cost up to 300,000 dollars, and Elon Musk, the eccentric billionaire and investor, bought 10,000 of these graphics processing units in preparation for starting a new AI technology company. This order alone has the potential to surge the prices and shares of a company.
Nvidia and AI gaming
Nvidia shares didn’t only enjoy the effects of the demand generated by artificial intelligence companies. It turns out that Nvidia Corporation has been leaning heavily on all types of artificial intelligence technologies in the last couple of years.
The company has been working on everything from generative AI to AI training, data analytics, and speech AI. A quick peek at the Nvidia Corporation’s AI-related services website and projects is more than enough to get someone confused, even dizzy. Also, Nvidia CEO Jensen Huang unveiled multiple AI projects and products in a two hour presentation in Taiwan.
Yet there’s this one product that Nvidia Corporation has revealed lately, and it alone bears the potential to revolutionize the gaming industry. This gaming-focused artificial intelligence technology is called Nvidia ACE. What is Nvidia ACE? It’s a groundbreaking real-time artificial intelligence (AI) technology that aims to enable real-time interactive AI characters.
The name is self-explanatory, but to elaborate a bit, Nvidia ACE enables the development of AI non-player characters (NPCs) in real-time, enhancing their interactivity through improvised voice dialogue and synchronized facial animations that seamlessly blend with the game world. By harnessing advanced AI algorithms, ACE offers unprecedented dynamic and personalized responses to player actions, creating a captivating and immersive gaming experience that surpasses anything seen before.
Although this AI technology may render multiple jobs obsolete and leave many people like writers, voice actors, animators, and more unemployed, it’s a giant leap forward regarding technology.
Imagine an open-world video game where instead of pre-scripted, pre-recorded, and limited dialogue, NPCs can react to whatever you do, answer whatever you ask, react to the player, their actions and influence, and the world around them in the game. Predicting how this will affect emergence and immersiveness is not very hard.
Combined with the fact that players are willing to pay more for games that feature real AI NPCs, it becomes easier to predict that such a technology will have a very high commercial value, both for the gamers and the game developers.
Speech AI lets the users develop real-time conversational AI workflows. Companies engage with their customers in numerous languages daily, accumulating billions of minutes of conversation. By integrating speech and translation AI technology into their applications, companies gain valuable insights from these interactions, improve their products and services, and deliver personalized real-time recommendations. Companies employ multilingual intelligent virtual assistants and digital avatars with customized domain-specific terminology and captivating brand voices to ensure round-the-clock support.
Generative AI enables the customization and deployment of pre-trained foundational models. The world is witnessing the remarkable rise of generative AI capabilities. It can summarize text, generate images, write code, and perform other incredible tasks.
Enterprise applications require AI technology solutions tailored to their specific domains, possessing a deep understanding of their business and the skills to accomplish high-value objectives. These models must scale across various business functions and continually learn as the organization expands and evolves. Generative AI models can capture and embody an organization’s intelligence.
AI Training enables cloud-based training of LLMs and generative AI models. Enterprises seeking to incorporate generative AI and LLMs into their business operations require specialized infrastructure to support scalable, multi-node training. This infrastructure should provide predictable and cost-effective performance. By integrating cutting-edge AI supercomputing capabilities with high-performance, low-latency network fabrics and tools that streamline the developer workflow, enterprises can achieve quicker time-to-solution for even the most complex models, ultimately resulting in a faster return on investment (ROI) for their AI initiatives.
Inference delivers revolutionary AI inference performance. NVIDIA provides the essential performance, efficiency, and responsiveness needed to advance AI inference in various environments: the cloud, data centers, network edges, and embedded devices. This solution caters to data scientists, application developers, and software infrastructure engineers focused on developing computer vision, speech recognition, natural language processing (NLP), generative AI, recommender systems, and other cutting-edge applications. Accelerate AI inference deployment with the comprehensive NVIDIA platform.
Data Analytics offers accelerated data science and delivers improvements across the end-to-end data analytics workflow, whether you’re transforming data for enterprise consumption or visualizing terabyte-scale data to understand a particular problem domain.
Data practitioners can use NVIDIA software to easily take advantage of GPU acceleration using their preferred toolset, bringing the power of high-performance computing to your organization with a minimal learning curve. By harnessing the power of high-performance data analytics, businesses can better serve their customers, develop products faster, and enable innovations across their enterprise.
The above examples are just the solutions available to the clients. Nvidia Corporation also has many artificial intelligence projects and AI-related technologies under development. The company even has a whole archive dedicated to artificial intelligence and machine learning research documents, publications, and articles.
What will AMD’s response be to this? As a PC gaming enthusiast, I’m very familiar with the history of the vendetta between AMD and Nvidia. Since Lise Su has taken over AMD, it has been on a hot streak and has taken multiple leaps forward financially and technologically. Did anyone in AMD see Nvidia’s huge breakthrough coming, or are they planning anything to answer the latest success of their long-time rival?
